Computational Intelligence in Optimization - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Computational Intelligence in Optimization write by Yoel Tenne. This book was released on 2010-06-30. Computational Intelligence in Optimization available in PDF, EPUB and Kindle. This collection of recent studies spans a range of computational intelligence applications, emphasizing their application to challenging real-world problems. Covers Intelligent agent-based algorithms, Hybrid intelligent systems, Machine learning and more.
Computational Intelligence in Expensive Optimization Problems
Computational Intelligence in Expensive Optimization Problems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Computational Intelligence in Expensive Optimization Problems write by Yoel Tenne. This book was released on 2010-03-10. Computational Intelligence in Expensive Optimization Problems available in PDF, EPUB and Kindle. In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such challenges include limited computational resource for simulation runs, complicated response surface of the simulation inputs-outputs, and etc. Under such difficulties, classical optimization and analysis methods may perform poorly. This motivates the application of computational intelligence methods such as evolutionary algorithms, neural networks and fuzzy logic, which often perform well in such settings. This is the first book to introduce the emerging field of computational intelligence in expensive optimization problems. Topics covered include: dedicated implementations of evolutionary algorithms, neural networks and fuzzy logic. reduction of expensive evaluations (modelling, variable-fidelity, fitness inheritance), frameworks for optimization (model management, complexity control, model selection), parallelization of algorithms (implementation issues on clusters, grids, parallel machines), incorporation of expert systems and human-system interface, single and multiobjective algorithms, data mining and statistical analysis, analysis of real-world cases (such as multidisciplinary design optimization). The edited book provides both theoretical treatments and real-world insights gained by experience, all contributed by leading researchers in the respective fields. As such, it is a comprehensive reference for researchers, practitioners, and advanced-level students interested in both the theory and practice of using computational intelligence for expensive optimization problems.
Computational Intelligence for Optimization
Computational Intelligence for Optimization - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Computational Intelligence for Optimization write by Nirwan Ansari. This book was released on 2012-12-06. Computational Intelligence for Optimization available in PDF, EPUB and Kindle. The field of optimization is interdisciplinary in nature, and has been making a significant impact on many disciplines. As a result, it is an indispensable tool for many practitioners in various fields. Conventional optimization techniques have been well established and widely published in many excellent textbooks. However, there are new techniques, such as neural networks, simulated anneal ing, stochastic machines, mean field theory, and genetic algorithms, which have been proven to be effective in solving global optimization problems. This book is intended to provide a technical description on the state-of-the-art development in advanced optimization techniques, specifically heuristic search, neural networks, simulated annealing, stochastic machines, mean field theory, and genetic algorithms, with emphasis on mathematical theory, implementa tion, and practical applications. The text is suitable for a first-year graduate course in electrical and computer engineering, computer science, and opera tional research programs. It may also be used as a reference for practicing engineers, scientists, operational researchers, and other specialists. This book is an outgrowth of a couple of special topic courses that we have been teaching for the past five years. In addition, it includes many results from our inter disciplinary research on the topic. The aforementioned advanced optimization techniques have received increasing attention over the last decade, but relatively few books have been produced.
Multi-Objective Optimization in Computational Intelligence: Theory and Practice
Multi-Objective Optimization in Computational Intelligence: Theory and Practice - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multi-Objective Optimization in Computational Intelligence: Theory and Practice write by Thu Bui, Lam. This book was released on 2008-05-31. Multi-Objective Optimization in Computational Intelligence: Theory and Practice available in PDF, EPUB and Kindle. Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large number of MO real-world applications. Multi-Objective Optimization in Computational Intelligence: Theory and Practice explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. This book provides scholars, academics, and practitioners with a fundamental, comprehensive collection of research on multi-objective optimization techniques, applications, and practices.
Computational Optimization, Methods and Algorithms
Computational Optimization, Methods and Algorithms - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Computational Optimization, Methods and Algorithms write by Slawomir Koziel. This book was released on 2011-06-17. Computational Optimization, Methods and Algorithms available in PDF, EPUB and Kindle. Computational optimization is an important paradigm with a wide range of applications. In virtually all branches of engineering and industry, we almost always try to optimize something - whether to minimize the cost and energy consumption, or to maximize profits, outputs, performance and efficiency. In many cases, this search for optimality is challenging, either because of the high computational cost of evaluating objectives and constraints, or because of the nonlinearity, multimodality, discontinuity and uncertainty of the problem functions in the real-world systems. Another complication is that most problems are often NP-hard, that is, the solution time for finding the optimum increases exponentially with the problem size. The development of efficient algorithms and specialized techniques that address these difficulties is of primary importance for contemporary engineering, science and industry. This book consists of 12 self-contained chapters, contributed from worldwide experts who are working in these exciting areas. The book strives to review and discuss the latest developments concerning optimization and modelling with a focus on methods and algorithms for computational optimization. It also covers well-chosen, real-world applications in science, engineering and industry. Main topics include derivative-free optimization, multi-objective evolutionary algorithms, surrogate-based methods, maximum simulated likelihood estimation, support vector machines, and metaheuristic algorithms. Application case studies include aerodynamic shape optimization, microwave engineering, black-box optimization, classification, economics, inventory optimization and structural optimization. This graduate level book can serve as an excellent reference for lecturers, researchers and students in computational science, engineering and industry.
